14 citations · 20 across the 16 of their papers we have counts for
9 papers · 1 filter
Systematic Evaluation of Time-Frequency Features for Binaural Sound Source Localization
Davoud Shariat Panah, Alessandro Ragano, Dan Barry +2
This study presents a systematic evaluation of time-frequency feature design for binaural sound source localization (SSL), focusing on how feature selection influences model perfor…
BINAQUAL: A Full-Reference Objective Localization Similarity Metric for Binaural Audio
Davoud Shariat Panah, Dan Barry, Alessandro Ragano +2
Spatial audio enhances immersion in applications such as virtual reality, augmented reality, gaming, and cinema by creating a three-dimensional auditory experience. Ensuring the sp…
Dialogue Understandability: Why are we streaming movies with subtitles?
Helard Becerra Martinez, Alessandro Ragano, Diptasree Debnath +4
Watching movies and TV shows with subtitles enabled is not simply down to audibility or speech intelligibility. A variety of evolving factors related to technological advances, cin…
Reduce, Reuse, Recycle: Is Perturbed Data better than Other Language augmentation for Low Resource Self-Supervised Speech Models
Asad Ullah, Alessandro Ragano, Andrew Hines
Self-supervised representation learning (SSRL) has demonstrated superior performance than supervised models for tasks including phoneme recognition. Training SSRL models poses a ch…
Learning Music Representations with wav2vec 2.0
Alessandro Ragano, Emmanouil Benetos, Andrew Hines
Learning music representations that are general-purpose offers the flexibility to finetune several downstream tasks using smaller datasets. The wav2vec 2.0 speech representation mo…
Exploring the influence of fine-tuning data on wav2vec 2.0 model for blind speech quality prediction
Helard Becerra, Alessandro Ragano, Andrew Hines
Recent studies have shown how self-supervised models can produce accurate speech quality predictions. Speech representations generated by the pre-trained wav2vec 2.0 model allows c…
A Comparison of Deep Learning MOS Predictors for Speech Synthesis Quality
Alessandro Ragano, Emmanouil Benetos, Michael Chinen +4
Speech synthesis quality prediction has made remarkable progress with the development of supervised and self-supervised learning (SSL) MOS predictors but some aspects related to th…
More for Less: Non-Intrusive Speech Quality Assessment with Limited Annotations
Alessandro Ragano, Emmanouil Benetos, Andrew Hines
Non-intrusive speech quality assessment is a crucial operation in multimedia applications. The scarcity of annotated data and the lack of a reference signal represent some of the m…
Audio Impairment Recognition Using a Correlation-Based Feature Representation
Alessandro Ragano, Emmanouil Benetos, Andrew Hines
Audio impairment recognition is based on finding noise in audio files and categorising the impairment type. Recently, significant performance improvement has been obtained thanks t…